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courses:cs366:syllabus [2020/01/08 17:03]
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 == Text == == Text ==
  
-  * Dan Jurafsky and James Martin, [[http://www.cs.colorado.edu/%7Emartin/slp.html | Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition  ]], Second Edition. Required. (available in the Book Store).+  * Dan Jurafsky and James Martin, [[http://www.cs.colorado.edu/%7Emartin/slp.html | Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition  ]], Second Edition, and [[https://web.stanford.edu/~jurafsky/slp3/ | selected chapters online from the upcoming 3rd edition]].
   * We will also use [[http://www.nltk.org/book/ | the online book associated with the Natural Language ToolKit (NLTK)]].   * We will also use [[http://www.nltk.org/book/ | the online book associated with the Natural Language ToolKit (NLTK)]].
  
 == Other useful books and materials == == Other useful books and materials ==
- +  * Dickinson, Brew, and Meuers. [[https://www.wiley.com/en-us/Language+and+Computers-p-9781405183055 | Language and Computers.]] Wiley Press. 
-  * Witten, I. H., Eibe, F., Hall, M.A. [[https://www.cs.vassar.edu/~cs366/docs/Data-Mining-Weka.pdf | Data Mining: Practical Machine Learning Tools and Techniques]], Third Edition.+
   * Manning, C. and Schütze, H.  [[https://nlp.stanford.edu/fsnlp/ | Foundations of Statistical Natural Language Processing.]] MIT Press.   * Manning, C. and Schütze, H.  [[https://nlp.stanford.edu/fsnlp/ | Foundations of Statistical Natural Language Processing.]] MIT Press.
 +  * Witten, I. H., Eibe, F., Hall, M.A. [[https://www.elsevier.com/books/data-mining/witten/978-0-12-804291-5 | Data Mining: Practical Machine Learning Tools and Techniques]], Fourth Edition.
   * Lutz and Ascher, [[http://shop.oreilly.com/product/9780596002817.do | Learning Python]], O'Reilly.   * Lutz and Ascher, [[http://shop.oreilly.com/product/9780596002817.do | Learning Python]], O'Reilly.
  
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   * The Natural Language Toolkit--NLTK (available [[http://nltk.org/install | here ]]) and the NLTK data (available [[http://nltk.org/data | here ]]). If not already installed on your computer, you will also need to install [[http://www.python.org/download/ | Python]].   * The Natural Language Toolkit--NLTK (available [[http://nltk.org/install | here ]]) and the NLTK data (available [[http://nltk.org/data | here ]]). If not already installed on your computer, you will also need to install [[http://www.python.org/download/ | Python]].
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-  * Weka for machine learning, available [[ http://sourceforge.net/projects/weka/ | here ]]. 
- 
-  * (optional) the General Architecture for Text Engineering (GATE), available [[http://gate.ac.uk|here]].  
  
 == Discussion == == Discussion ==
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 == Grades == == Grades ==
  
-Grades will be determined on the basis of performance on four assignments (40%), a final project and presentation (50%), and homework (10%). The [[courses:cs3662020B:schedule|Schedule of Lectures, Readings, and Assignments]] contains links to assignments, homework, lecture slides, and specifies due dates, etc. Information may also be disseminated via the [[https://groups.google.com/forum/#!forum/cs366-computational-linguistics-2020 | CS366 mailing list]].+Grades will be determined on the basis of performance on four assignments (40%), a final project and presentation (50%), and homework (10%). The [[https://www.cs.vassar.edu/~cs366/schedule |Schedule of Lectures, Readings, and Assignments]] contains links to assignments, homework, lecture slides, etc. Information may also be disseminated via the [[https://groups.google.com/forum/#!forum/cs366-computational-linguistics-2020 | CS366 mailing list]].